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import androidx.compose.animation.core.Animatable
import androidx.compose.animation.core.EaseInOutQuad
import androidx.compose.animation.core.FastOutSlowInEasing
import androidx.compose.animation.core.LinearEasing
import androidx.compose.animation.core.RepeatMode
import androidx.compose.animation.core.Spring
import androidx.compose.animation.core.animateFloat
import androidx.compose.animation.core.infiniteRepeatable
import androidx.compose.animation.core.rememberInfiniteTransition
@intenzemotion
intenzemotion / hide-edge-rounded-corners.ps1
Last active August 8, 2026 07:34
Hide Edge v149 forced rounded corners. Additionally hide red dot on profile icon too.
# This script must be run as Administrator to update some shortcut paths. Checking it first...
$IsAdmin = ([Security.Principal.WindowsPrincipal] [Security.Principal.WindowsIdentity]::GetCurrent()).IsInRole(
[Security.Principal.WindowsBuiltInRole]::Administrator
)
if (-not $IsAdmin) {
Write-Host "Not running as Administrator. Some shortcuts may fail to update." -ForegroundColor Yellow
Write-Host ""
}
# This is your Edge path, it should be installed here (if you're on Stable channel).
@0006969
0006969 / internetarchive.png
Created August 8, 2026 07:30
Public (SPKI base64) / SHA-512 / Signature (RSA)
Public key
MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA6SGhr3n+JW/IHf0pR9WCdiw6f6NdOy+jyX/YGzicap2Vqz5Ha9SDFCEhA+ZEGOeXVhfHywHrHBmOlJn3+xctZqnOFX/sn37Lfp2/m1Wya7VNARgmej4rOT+j74KO3DbcCCGilzVBjVdfc8c9oijIPdu5lDiZf8XhZSGuaPTYG3K1a9EhrHQQfHinDWn8uPNeqSUBl8sFq9Ox683YOnRAsPkU9Ip16qUCi9wnw4FyLZX00HZFgTDeTSfIPLo6LDDUndGRwY3S1W+t7z1NolMzhtBlIs5LO9pAEmXQ+xorAIwwZgSiSn4zRE30Y0uxZkL9eFCzyfKrbQNn8xTXgOrEYQIDAQAB
SHA-512
5a01af61c90cd1b8e679a54396555abc8f3663c709476de5b6fbd2ac988789379459d77af14afdbcaa1650349f4475f1b92c64fe71bc3c81a43d5f72072af8c5
Signature
vfIiWf2253ZH1iofzEBwR9kZZv22duFYPLav1E4qirklJjvb4Q+v5PntKi39OPpwz/oSHUmgJKHzfLCtrju6bWV0HeplG2sPp+0TAWc4XDiOykMW9304C/yDPZeje+3Oe2IDuoUNX6lLJuT3TyoRe1QatH6OkjX9iSMv5nkwAbnCFKmdaWvZvKL90M4Bg37o7yXgRLYWZRFzb0yPavDy/6VJ/IJ7VQFVZxKsLSq/l0GTqE6Y/+HY538Kw0G9SvGG7QHtVOxy1+d7hNNVzvxa6wZ44qg1TrqsAG0RlB5pKnq4hsbWlaMhks1lJ54wcvgt1YQZqu5Z3YXEdl1/FvezEQ==
@LukasMFR
LukasMFR / chatgpt-conversation-exporter.js
Created December 12, 2025 12:36
JavaScript snippet to export a ChatGPT conversation from the web UI to a clean Markdown file, with correct user/assistant attribution, code block preservation, and basic media placeholders. Designed to be run directly in the browser console (Safari/Chrome/Firefox).
(() => {
function formatDate(date = new Date()) {
return date.toISOString().split("T")[0];
}
function escapeMarkdown(text) {
return text
.replace(/\\/g, "\\\\")
.replace(/\*/g, "\\*")
.replace(/_/g, "\\_")
@rvrsh3ll
rvrsh3ll / windows-keys.md
Created February 18, 2024 22:44
Windows Product Keys

NOTE

These are NOT product / license keys that are valid for Windows activation.
These keys only select the edition of Windows to install during setup, but they do not activate or license the installation.

Index

use std::{
path::{Path, PathBuf},
str::FromStr,
};
use coolfindpattern::pattern;
use pelite::pe::Pe;
use simplelog::Config;
use windows_registry::{CURRENT_USER, LOCAL_MACHINE};
@ankushian
ankushian / AV1Encoding.md
Created June 21, 2025 18:34
AV1 encoding pocket guide (using SVT-AV1)

Tenets of AV1 Encoding

AV1 is a next-generation video codec developed by Alliance of Open Media to facilitate VOD, storage and live-streaming. It's usually paired with Opus audio codec, stored in MP4 (ISOBMFF) or streamed using HLS (HTTP Live Streaming). SVT-AV1 is currently the best production quality encoder available (the matter of discusssion here).

Presets

Quoting the SVT-AV1 documentation:

Presets control how many efficiency features are used during the encoding process, and the intensity with which those features are used. Lower presets use more features and produce a more efficient file (smaller file, for a given visual quality). However, lower presets also require more compute time during the encode process. If a file is to be widely distributed, it can be worth it to use very low presets, while high presets allow fast encoding, such as for real-time applications. >

@Naxdy
Naxdy / sysprompt.md
Last active August 8, 2026 07:21
Minimax H3 Prompt Enhancer

Role

You are a prompt-enrichment engine that sits between a user's raw creative request and MiniMax H3, a generative model that synthesizes video AND synchronized stereo audio together. Your role mirrors MiniMax's official "H3-Context-IR": deeply understand and refine the multimodal input, reason about how the pieces relate to each other and to the intended output, and serialize your understanding into a structured "production brief" that H3-Base can consume directly. You perform instruction parsing, cross-modal association, temporal understanding, and complex logical reasoning over the material you are given. Without deviating from the user's original intent, you may supplement missing or underspecified semantic details where appropriate. You convert everything into a single, maximally detailed and unambiguous brief, formatted exactly as specified below. You DO NOT generate media yourself. You ONLY OUTPUT THE BRIEF TEXT, nothing else — no preamble, no explanation, no markdown fences, no JSON wrapper.

Wh

@jeremyjohn
jeremyjohn / install_and_disable_claude_desktop_background_cowork_service.md
Created August 8, 2026 07:17
Install and Disable Windows Claude Desktop Cowork Background VM Service

Install and Disable Windows Claude Desktop Cowork Background VM Service

Tested on:

  • Windows 10 x64, build 19045
  • Claude Desktop 1.26832.0.0

Goal

Install and use Claude Desktop and Claude Code while disabling Cowork and preventing the Cowork background VM service from running.

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.